artículo de publicación periódica.page.titleprefix
Detection of atypical response trajectories in biomedical longitudinal databases

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dc.contributor.authorPantazis, Lucio José
dc.contributor.authorGarcía, Rafael Antonio
dc.date.accessioned2023-12-07T19:36:25Z
dc.date.available2023-12-07T19:36:25Z
dc.date.issued2022-10-24
dc.descriptionDetection of atypical response trajectories in biomedical longitudinal databases
dc.description.abstractMany health care professionals and institutions manage longitudinal databases, involving follow-ups for different patients over time. Longitudinal data frequently manifest additional complexities such as high variability, correlated measurements and missing data. Mixed effects models have been widely used to overcome these difficulties. This work proposes the use of linear mixed effects models as a tool that allows to search conceptually different types of anomalies in the data simultaneously.
dc.description.sponsorshipConsejo Nacional de Investigaciones Científicas y Técnicas (CONICET)
dc.identifier.doihttps://doi.org/10.1515/ijb-2020-0076
dc.identifier.urihttps://ri.itba.edu.ar/handle/123456789/4229
dc.language.isoen
dc.publisherDe Gruyter
dc.subjectLONGITUDINAL DATA
dc.subjectMIXED EFFECTS MODELS
dc.subjectOUTLIER DETECTION
dc.subjectDATA LONGITUDINAL
dc.subjectMODELO DE EFECTOS MIXTOS
dc.titleDetection of atypical response trajectories in biomedical longitudinal databases
dc.typeArtículo de Publicación Periódica
dspace.entity.typeArtículo de Publicación Periódica
itba.description.filiationFil: Pantazis, Lucio José. Instituto Tecnológico de Buenos Aires; Argentina.

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